Topic
Sleep (system call)
About: Sleep (system call) is a research topic. Over the lifetime, 2633 publications have been published within this topic receiving 27806 citations. The topic is also known as: Sleep() & sleep().
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TL;DR: Wang et al. as mentioned in this paper designed a sleep staging network named SleepContextNet for sleep stage sequence, which utilizes the temporal dependencies among the EEG epochs effectively and improves the accuracy of sleep stages.
7 citations
18 May 2020
TL;DR: In this article, the authors proposed and validated an approach that combines both subjective and objective measures of sleep, accounting for a person's lifestyle and ties it to meaningful and measurable carryover effects such as daytime alertness and working memory.
Abstract: Most commercial sleep sensors typically rely on population-level data and focus on recommendations based on objective metrics such as sleep duration or sleep efficiency However, there is inter-individual trait-variability to sleep and people's sleep habits are individualized To prompt users to adopt habits that improve sleep health, meaningful sleep feedback must not only provide evidence of how users' behaviors affect their sleep quality, as objectified by some of the metrics, but also show how carry-over effects of sleep affect daytime cognitive function In this paper, we propose and validate an approach that combines both subjective and objective measures of sleep, accounting for a person's lifestyle and ties it to meaningful and measurable carryover effects such as daytime alertness and working memory Our approach is based on the medical community's Ru-SATED framework, which characterizes sleep through six dimensions: Regularity, Satisfaction, Alertness, Timing, Efficiency and Duration Using data collected by a smart phone app: SleepApp, with a suite of ecological momentary assessment tests from 9 participants over 14 days, we demonstrate how sleep health can be contextualized to the individual lifestyle and actionable feedback can be generated In a follow up survey with 57 respondents, we show how the actionable feedback generated by SleepApp can encourage in users the intent to make adjustments to their sleep habits that may impact their daytime cognitive function
7 citations
TL;DR: Focus on long-term memory and cognitive control processes, and examines neural response changes related to these behavioral changes induced by sleep deprivation based on human fMRI studies to determine the brain regions in which neural responses increase or decrease as a consequence of sleep deprivation.
Abstract: Sleep deprivation is known to have adverse effects on various cognitive abilities. In particular, a lack of sleep has been reported to disrupt memory consolidation and cognitive control functions. Here, focusing on long-term memory and cognitive control processes, we review the consistency and reliability of the results of previous studies of sleep deprivation effects on behavioral performance with variations in the types of stimuli and tasks. Moreover, we examine neural response changes related to these behavioral changes induced by sleep deprivation based on human fMRI studies to determine the brain regions in which neural responses increase or decrease as a consequence of sleep deprivation. Additionally, we discuss about the possibility that light as an environmentally influential factor affects our sleep cycles and related cognitive processes.
7 citations
Patent•
28 Dec 1990
TL;DR: In this article, the authors proposed to reduce power consumption by operating the only wake-up frame detection circuit when each slave transmitter is waited and operating the entire circuit when a wakeup frame is detected.
Abstract: PURPOSE: To reduce power consumption by operating the only wake-up frame detection circuit when each slave transmitter is waited and operating the entire circuit when a wake-up frame is detected. CONSTITUTION: When a slave transmitter 5n is turned on, a sleep stand-by mode is selected. The first-step amplifier of an O/E converter 8 and a wake-up detection circuit 13 start operating. When the wake-up frame is detected by the photo diode of the first-step amplifier, each circuit is actuated in the prescribed timing, and a timer 14 is operated. Immediately after the prescribed count-up of the timer 14, it is returned to a sleep stand-by mode. Thus, the power consumption can be reduced. Moreover, by delaying the timing from a waiting state to an operational state in the order of slave number, unnecessary waiting time can be reduced. COPYRIGHT: (C)1992,JPO&Japio
7 citations
TL;DR: This paper showed that post-learning sleep is regulated by two opposing output neurons (MBONs) from the Mushroom Body (MB) which encode a measure of learning, and these MB outputs are integrated by SFS neurons, which excite vFBs to promote sleep after prolonged but not short training.
Abstract: Animals retain some but not all experiences in long-term memory (LTM). Sleep supports LTM retention across animal species. It is well established that learning experiences enhance post-learning sleep. However, the underlying mechanisms of how learning mediates sleep for memory retention are not clear. Drosophila males display increased amounts of sleep after courtship learning. Courtship learning depends on Mushroom Body (MB) neurons, and post-learning sleep is mediated by the sleep-promoting ventral Fan-Shaped Body neurons (vFBs). We show that post-learning sleep is regulated by two opposing output neurons (MBONs) from the MB, which encode a measure of learning. Excitatory MBONs-γ2α'1 becomes increasingly active upon increasing time of learning, whereas inhibitory MBONs-β'2mp is activated only by a short learning experience. These MB outputs are integrated by SFS neurons, which excite vFBs to promote sleep after prolonged but not short training. This circuit may ensure that only longer or more intense learning experiences induce sleep and are thereby consolidated into LTM.
7 citations